Sharing scientific and data capture files of gigabyte and terabyte size in conventional data grid systems is inefficient because conventional approaches copy the entire shared file to a user's local storage even when only a tiny file fragment is required. Such transfer schemes consume unnecessary data transmission time and local storage space, with the additional problem of maintaining replica synchronization. Traditionally, replica consistency treats shared files as read-only, consequently sacrificing guaranteed replica consistency. This paper presents a DSM-based fragmented data sharing framework called "Spigot" which transfers only the necessary fragments of large files on user demand, thereby reducing data transmission time, wasted network bandwidth and required storage space. Data waiting time is further reduced by overlapping data transmission and data analysis. The DSM concept maintains replica synchronization. Real experiments show reduced turnaround time in data-intensive applications, particularly when fragment size is low and analysis time and network latency are high.
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